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Quantum Computing Research Scientist

Nexus Labs
Austin
Estimated Salary
USD 180.000 – USD 250.000
Live Update
29 Juni 2026
Deadline
29 Jun 2027

Job Description

Join Nexus Labs at the forefront of technological evolution as we pioneer quantum computing solutions for 2026 and beyond. Our Austin-based research hub is seeking visionary Quantum Computing Research Scientists to develop breakthrough algorithms and hardware architectures. You'll collaborate with Nobel laureates and industry disruptors in a state-of-the-art facility, pushing the boundaries of computational physics and information theory.

We offer unparalleled resources including access to 128-qubit quantum processors, dedicated research budgets, and patent support for your innovations. This role is perfect for those who thrive at the intersection of theoretical physics and practical application.

Responsibilities

  • Design and implement novel quantum algorithms for optimization and simulation problems
  • Develop error-correction protocols for next-generation quantum processors
  • Lead cross-functional teams to translate theoretical models into scalable hardware solutions
  • Publish research in top-tier journals and present at global quantum computing conferences
  • Collaborate with hardware teams to co-design quantum processor architectures
  • Secure government and private research grants for experimental validation

Qualifications

  • PhD in Quantum Physics, Computer Science, or related field with 3+ years post-doctoral experience
  • Published research in Nature/Science/Physical Review on quantum systems
  • Proficiency in quantum programming languages (Q#, Qiskit, Cirq)
  • Demonstrated expertise in quantum error correction and fault-tolerant computing
  • Experience with cryogenic quantum hardware or superconducting qubits
  • Track record of securing competitive research grants
  • Strong background in topological quantum computing or quantum machine learning

Required Skills

Quantum Computing Quantum Algorithms Error Correction Qiskit Cirq Cryogenic Engineering Theoretical Physics Machine Learning

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